… hierarchy levels. In this paper, we propose a novel semi-supervised hierarchical clustering
… We establish the connection between hierarchical clustering and ultra-metric transformation …

… and related work of CHAMELEON algorithm and clustering ensemble. In Section 3, we
present an unsupervised and semi-supervised clustering ensemble model, and give an …

… clustering, as most existing semi-supervised clustering methods are modified versions of
k-means clustering. … of the most common hierarchical clustering methods, although many other …

… clustering results of the abovementioned hierarchical clustering method and the cluster-thenlabel
semi-supervised … A clustering algorithm with a Gaussian test and distances metric are …

… of agglomerative hierarchical clustering as well as non-hierarchical clustering for semi-supervised
classification is given. Two different formulations for semi-supervised classification are …

… , semi-supervised clustering gradually attracts more attention and becomes a new research
hotpot. In the 1960s, the emergence of hierarchical clustering … by semi-supervised clustering …

… tags which greatly decreases the clustering performance while increases the … step semi-supervised
hierarchical clustering algorithm, Personalized Hierarchical Theme-based Clustering …

… In this paper, we present a semi-supervised hierarchical … a number of hierarchical clusters
iteratively to learn cluster-level CNNs … similar images into the same cluster, which relieves the …

… labeled by using semi-supervised learning for both … semi-supervised hierarchical clustering
(SSHC [6]) method 85 that can model each class of cells as a collection of a few 86 clusters …

… into the hierarchical clustering process. Bade et al. [1] present a semi-supervised hierarchical
clustering approach, which is mixed with a biased clustering process in order to organize …